A suite of Stata programs for network meta-analysis

Similar presentations

1 A suite of Stata programs for network meta-analysisUK Stata users’ GroupLondon, 13th September 2013Ian WhiteMRC Biostatistics Unit, Cambridge, UK20 mins talk + 10 mins discussionAbstract: Network meta-analysis involves synthesising the scientific literature comparing several treatments. Typically, two-arm and three-arm randomised trials are synthesised, and the aim is to compare treatments that have not been directly compared, and often to rank the treatments. A difficulty is that the network may be inconsistent, and ways to assess this are required.In the past, network meta-analysis models have been fitted using Bayesian methods, typically in WinBUGS. I have recently shown how they may be expressed as multivariate meta-analysis models and hence fitted using mvmeta. However, various challenges remain, including getting the data set up in the correct format; parameterising the inconsistency model; and making good graphical displays of complex data and results. I will show how a new suite of Stata programs, network, meets these challenges, and I will illustrate its use with examples.

6 But actually the data are more complicated …studydAnAdBnBdCnCdDnD19140231013821178128529170379702776944186712153558116191466757313637147106205585492371561334810031982695391713110713410311415187355045847367516691177548886464210776162902023434494322663212776742455Trials compared 4 different interventions to help smokers quit:A="No contact"B="Self help"C="Individual counselling"D="Group counselling"

8 Network meta-analysisIf we want to make best use of the evidence, we need to analyse all the evidence jointlyMay enable us to identify the best treatmentA potential problem is inconsistency: what if the indirect evidence disagrees with the direct evidence?The main statistical challenges are:formulating and fitting models that allow for heterogeneity and inconsistencyassessing inconsistency and (if found) finding ways to handle itLess-statistical challenges includedefining the scope of the problem (which treatments to include, what patient groups, what outcomes)

12 Data format 2: AugmentedstudydesignyByCyDSBBSBCSBDSCCSCDSDD1ACD.1.0510.1290.1710.1190.2273AB-0.0160.02940.3940.10750.7030.1956AC2.2020.020same reference treatment (A) in all designssimplifies modelling: just need the means of yB, yC, yDproblems arise for studies with no arm A: I “augment” by giving them a very small amount of data in arm A:studydesignyByCyDSBBSBCSBDSCCSCDSDD2BCD0.0010.22521BC-0.152.22BD1.04323CD0.68124-0.405

13 Fitting network meta-analysesIn the past, the models have been fitted using WinBUGSbecause frequentist alternatives have not been availablehas made network meta-analysis inaccessible to non-statisticiansNow, consistency and inconsistency models can be fitted for both data formats using multivariate meta-analysis or multivariate meta-regressionusing my mvmetaParameterising the consistency model for “augmented” format is easyAllowing for inconsistency and “standard” format is trickier …

14 Aims of the network suiteAutomatically convert network data to the correct format for multivariate meta-analysisAutomatically set up mvmeta models for consistency and inconsistency, and run themProvide graphical displays to aid understanding of data and resultsHandle both standard and augmented formats, and convert between them, in order to demonstrate their equivalenceInterface with other Stata software for network meta-analysis

27 Graphicscan convert to “pairs” format (one record per contrast per study) and access the routines by Anna Chaimani & Georgia Salanti (e.g. networkplot graphs the network showing which treatments and contrasts are represented in more trialsNext: my extension of the standard forest plot …

31 A difficultyIn network forest: I need to make the symbol sizes proportional to 1/se2 (using [aweight=1/se^2])across all panelsacross all plots (i.e. the different colours)This doesn’t happen automaticallyI think scatter makes the largest symbol in each panel the same sizeI’m still not sure I have got it right …